2 citations · 5 across the 22 of their papers we have counts for
10 papers · 1 filter
CamWorldQA: Perceptual Quality Assessment of Camera-Controlled World Video Generation
Yunhe Li, Likun Wu, Sijing Wu +5
Recent advances in generative video models have enabled camera-controlled world video generation, allowing models to synthesize videos under user-defined camera trajectories. Howev…
PCQA-R1: Advancing Generalized 3D Point Cloud Quality Assessment with Reinforcement Learning
Kangning Ye, Yunhao Li, Sijing Wu +2
No-reference point cloud quality assessment (PCQA) has been an active topic in recent years and is used to measure and optimize the visual experience of point clouds. However, larg…
FMReward: Aligning and Evaluating Audio-Driven 3D Facial Animation with Human Preferences
Sijing Wu, Yunhao Li, Zhilin Gao +4
Audio-driven 3D facial animation is essential for advancing immersion and interactivity in virtual experiences. Although recent advances have shown promising capabilities, the trai…
Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model
Sijing Wu, Yunhao Li, Huiyu Duan +4
AI-generated human-centric videos play a crucial role in a wide range of modern applications. However, they often suffer from quality issues and semantic mismatches, underscoring t…
LoViF 2026 The First Challenge on Holistic Quality Assessment for 4D World Model (PhyScore)
Wei Luo, Yiting Lu, Xin Li +32
This paper reports on the LoViF 2026 PhyScore challenge, a competition on holistic quality assessment of world-model-generated videos across both 2D and 4D generation settings. The…
Surveillance Facial Image Quality Assessment: A Multi-dimensional Dataset and Lightweight Model
Yanwei Jiang, Wei Sun, Yingjie Zhou +8
Surveillance facial images are often captured under unconstrained conditions, resulting in severe quality degradation due to factors such as low resolution, motion blur, occlusion,…
VideoAesBench: Benchmarking the Video Aesthetics Perception Capabilities of Large Multimodal Models
Yunhao Li, Sijing Wu, Zhilin Gao +5
Large multimodal models (LMMs) have demonstrated outstanding capabilities in various visual perception tasks, which has in turn made the evaluation of LMMs significant. However, th…
SFQA: A Comprehensive Perceptual Quality Assessment Dataset for Singing Face Generation
Zhilin Gao, Yunhao Li, Sijing Wu +3
The Talking Face Generation task has enormous potential for various applications in digital humans and agents, etc. Singing, as a common facial movement second only to talking, can…
Q-Bench-Portrait: Benchmarking Multimodal Large Language Models on Portrait Image Quality Perception
Sijing Wu, Yunhao Li, Zicheng Zhang +5
Recent advances in multimodal large language models (MLLMs) have demonstrated impressive performance on existing low-level vision benchmarks, which primarily focus on generic image…
VTONQA: A Multi-Dimensional Quality Assessment Dataset for Virtual Try-on
Xinyi Wei, Sijing Wu, Zitong Xu +4
With the rapid development of e-commerce and digital fashion, image-based virtual try-on (VTON) has attracted increasing attention. However, existing VTON models often suffer from…